Pathogen-Specific Local Immune Fingerprints Diagnose Bacterial Infection in Peritoneal Dialysis Patients

免疫系统 免疫学 腹膜透析 腹膜炎 病菌 生物 医学 内科学
作者
Chan‐Yu Lin,Gareth Roberts,Matt Morgan,Kieron Donovan,Nicholas Topley,Matthias Eberl
出处
期刊:Journal of The American Society of Nephrology [American Society of Nephrology]
卷期号:24 (12): 2002-2009 被引量:57
标识
DOI:10.1681/asn.2013040332
摘要

Accurate and timely diagnosis of bacterial infection is crucial for effective and targeted treatment, yet routine microbiological identification is inefficient and often delayed to an extent that makes it clinically unhelpful. The immune system is capable of a rapid, sensitive and specific detection of a broad spectrum of microbes, which has been optimized over millions of years of evolution. A patient's early immune response is therefore likely to provide far better insight into the true nature and severity of microbial infections than conventional tests. To assess the diagnostic potential of pathogen-specific immune responses, we characterized the local responses of 52 adult patients during episodes of acute peritoneal dialysis (PD)–associated peritonitis by multicolor flow cytometry and multiplex ELISA, and defined the immunologic signatures in relation to standard microbiological culture results and to clinical outcomes. We provide evidence that unique local “immune fingerprints” characteristic of individual organisms are evident in PD patients on the day of presentation with acute peritonitis and discriminate between culture-negative, Gram-positive, and Gram-negative episodes of infection. Those humoral and cellular parameters with the most promise for defining disease-specific immune fingerprints include the local levels of IL-1β, IL-10, IL-22, TNF-α, and CXCL10, as well as the frequency of local γδ T cells and the relative proportion of neutrophils and monocytes/macrophages among total peritoneal cells. Our data provide proof of concept for the feasibility of using immune fingerprints to inform the design of point-of-care tests that will allow rapid and accurate infection identification and facilitate targeted antibiotic prescription and improved patient management.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
mzk发布了新的文献求助10
刚刚
芝士肉肉丸完成签到,获得积分10
2秒前
充电宝应助言午采纳,获得10
2秒前
大模型应助丹丹采纳,获得10
3秒前
liuzhuohao应助丹丹采纳,获得10
3秒前
汉堡包应助丹丹采纳,获得10
3秒前
天天快乐应助丹丹采纳,获得10
3秒前
斯文败类应助丹丹采纳,获得10
3秒前
科研通AI6.2应助丹丹采纳,获得10
3秒前
科研通AI6.4应助丹丹采纳,获得10
3秒前
科研通AI6.3应助丹丹采纳,获得10
3秒前
丘比特应助丹丹采纳,获得10
3秒前
星辰大海应助丹丹采纳,获得10
3秒前
丁丁发布了新的文献求助10
3秒前
科研通AI6.2应助东郭凝蝶采纳,获得10
4秒前
5秒前
羊羊羊发布了新的文献求助10
5秒前
6秒前
青衫烟雨客完成签到 ,获得积分10
6秒前
好嘞完成签到,获得积分10
6秒前
pjwl完成签到 ,获得积分10
7秒前
uniquelin完成签到,获得积分10
8秒前
小马甲应助wuxiaochen采纳,获得10
9秒前
充电宝应助YuanlinDeng采纳,获得30
10秒前
德力达发布了新的文献求助10
10秒前
科研通AI6.4应助丹丹采纳,获得10
10秒前
科研通AI6.4应助丹丹采纳,获得10
10秒前
思源应助丹丹采纳,获得10
11秒前
科研通AI6.2应助丹丹采纳,获得10
11秒前
NexusExplorer应助丹丹采纳,获得10
11秒前
上官若男应助丹丹采纳,获得10
11秒前
Hello应助丹丹采纳,获得10
11秒前
11秒前
科研通AI6.3应助丹丹采纳,获得10
11秒前
11秒前
情怀应助丹丹采纳,获得10
11秒前
科研通AI6.2应助丹丹采纳,获得10
12秒前
杨武天一发布了新的文献求助10
12秒前
Kao应助big_fi采纳,获得10
13秒前
jawa发布了新的文献求助30
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Nondestructive Testing Handbook: Vol. 4, Thermal and Infrared Testing (IR), 4th ed 800
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 590
Évora na Idade Média 555
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Radical Reactions 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7368780
求助须知:如何正确求助?哪些是违规求助? 8976646
关于积分的说明 19084920
捐赠科研通 7012136
什么是DOI,文献DOI怎么找? 3224733
关于科研通互助平台的介绍 2388093
邀请新用户注册赠送积分活动 2205330